What is Data Driven Marketing?
Data-driven marketing is defined as“analyzingbig data to understand and predict customer behaviour, then translating that insight into a targeted marketing strategy to lead the way forward.”(Source:Everstring)
Data-driven marketing strategy is a marketing strategy that uses customer insights to inform marketing and business decisions. It involves:
- Testing and analysing data
- Leveraging that data to refine and develop a targeted marketing strategy.
Many marketers gather data about their marketing efforts through platforms such as Google Analytics, Facebook Insights, and Google Ads reports to measure the effectiveness of their marketing campaigns. But only some marketers actively test different strategies and compare results to identify business opportunities and optimise for competitive advantage.
They“analysedata” but fail to leverage it to predict customer behaviour or translate it into a targeted strategy.
Most marketers analyse data to see if their campaign worked.
Smart marketers strategically leverage data to predict behaviour and make their campaign work.
When data is used to inform marketing strategy, marketers can:
- Identify and resolve pain points and business opportunities
- Maximise advertising ROI.
- Leverage insights unique to their own customers
- Benefit from first-mover competitive advantage by quickly identifying trends and future behaviour.
Why Should You Have A Data-Driven Marketing Strategy?
Data-driven marketing gives marketers strategic insights to create highly personalised campaigns, which have been proven to perform better than non-personalised campaigns. Marketers that exceeded their revenue goals in 2017 used personalisation 83% of the time.(Source:Forbes).
Using data helps you find unique insights about your customers and campaigns, that you might have otherwise missed. You can identify which marketing messages resonate most with customers, find segments of the market who are interested in your products that you could have overlooked, and identify demographics, behaviour and future needs of your customers to help inform your marketing decisions and deliver greater value to customers.
How to Start Building a Data-Driven Strategy
Creating a data driven marketing strategy may sound overwhelming, but its simple to start by analysing the data you already have - Google analytics, social media, google ads, and looking for patterns.
You can learn a lot by testing different messages, locations, creative and customer segments against each other. When building a data-driven strategy, keep these guidelines in mind:
- Do: Always Analyse Campaign Results
Your previous marketing campaigns are your best source of data. They show you how people respond to your specific marketing messages and products.
Here are some questions to ask yourself about each campaign:
- Which channel(s) performed better than others?
- Did some locations, age groups, or demographics perform better than others?
- Did some interest or affinity groups perform better than others? Did any surprise you?
- Were there any groups with high click throughs but a low conversion rate?
- Were there any groups with low click throughs but a high conversion rate?
- What was the last thing users completed before abandoning the conversion?
- How did your messages compare to other competitors?
- How did the campaign perform compared to previous campaigns you have run?
- Did users mostly view your campaign from mobile or desktop? Android or iPhone?
- Did some types of creative / photos perform better than others?
- Don’t: wait till the campaign is over to start learning.
If you wait until the campaign is over to analyse results in detail, you could miss out on valuable insights that you could have actioned during the campaign to improve profitability and reach. By proactively monitoring detailed stats throughout the campaign duration, marketers can make small changes throughout the campaign to reduce unprofitable spend and improve targeting, messaging and ad effectiveness.
To improve your campaign:
- Identify your best performing ad copies, keywords and ad groups.
- Identify your worst performing ad copies, keywords and ad groups.
- Watch out for high click through - low conversion ad groups in lead generation campaigns.
- A/B test copy and targeting to isolate the cause of the high / low performance and improve the response rate.
- Do: cross credit learnings.
Previous campaigns offer valuable insights to begin optimising your campaign before you even begin. Analyse previous campaigns for insights on targeting, messaging and creative, and use them to help refine your new campaign strategy.
While different channels need to be treated differently, avoid the temptation to write off all insights from a campaign on a different channel as irrelevant. These can still offer insights into the types of customers you resonate with and the messages and CTA’s that they respond to.
- Don’t: assume you know everything.
Once you’ve run several campaigns, you have a clear idea of your target market, messaging and targeting. However, don’t be afraid to step out of the box.
Campaigns that are compelling, engaging and resonating step away from the status quo, moving away from predictability to creativity and innovation, to create new customer experiences.
The market changes, and smart marketers watch the data, and their customers, to look for opportunities, so they can proactively lead change. If you are not proactive, you are reactive. Reactive marketers lose the first-mover advantage.
- Do: Optimise for customer experience.
Data offers insights into what people do - what they clicked on, how they converted, which message they responded to, and who they are, their age, location, gender, interests, but not why they do what they do. Data alone cannot replace human connection. Marketers need to think beyond the numbers alone to optimise for customer experience. What do customers need? What do they want? How can we best meet their needs?
Remember there are people behind the numbers.
- Don’t assume correlation is causation.
Patterns can be deceiving. Each marketing campaign is influenced by a wide range of factors. When making changes to your campaign, its easy to assume that a change in traffic that coincided with a change in the campaign was a direct result of the change, but this is not always the case.
Jumping to conclusions can lead to missed opportunity or wasted spend - you could cut out a profitable segment of your audience or put too much weight on a segment that is not as profitable as you think. This is especially important with small budgets and short timeframes - learning phases of campaigns, delayed reporting, and small numbers of impressions and clicks can skew results.
False decisions can be minimised by calculating statistical significance, using a larger sample size, and measuring over a longer time frame. If you use automated rules, consider adding one that will stop unprofitable campaigns and restart profitable campaigns that have been prematurely switched off.
- Do: Automate some of the process to save time.
Automated rules are an easy way to alert yourself to unusual campaign activity and minimise the impact of unprofitable segments on the overall campaign budget. You can set up automated rules to alert you of unprofitable ads, unusual changes to spend, sudden traffic spikes or dips, and campaigns generating click throughs without conversions, so nothing is missed.
- Don’t: only measure vanity metrics.
Metrics such as likes and impressions are useful, especially in brand awareness campaigns, but it’s more important to measure metrics that determine the real impact to your business. Metrics such as conversion rate, cost per lead, cost per conversion, cost per acquisition, customer lifetime value can help you determine if a campaign is profitable, or just generating attention. If users are engaging with the campaign but failing to convert, it’s a good idea to step back and look for choke-points or objections where you aren’t fully meeting customer needs.
Data is your greatest ally in digital strategy. Leveraging data will help you optimise your brand, product and your advertising to reach customers as effectively as possible.
Marketers who are committed to data-driven strategy position themselves for innovation, problem solving and competitive advantage.